A Ribosomal ATPase Is a Target for Hygromycin B Inhibition on <i>Escherichia coli</i> Ribosomes
Bibliographic record
Abstract
We demonstrate that the transfer of fully charged aminoacyl-tRNAs into peptides directed by the MS2 RNA template requires both ATP and GTP, initiation factors (IF1, IF2, and IF3), elongation factors (EF-Tu, EF-Ts, and EF-G), and the ribosomal ATPase (RbbA). The nonhydrolyzable analogue AMPPCP inhibits the reactions, suggesting that hydrolysis of ATP is required for synthesis. The RbbA protein occurs bound to ribosomes and stimulates the ATPase activity of Escherichia coli 70S and 30S particles. The gene encoding RbbA harbors four ATP binding domains; the C-terminal half of the protein bears extensive sequence similarity to EF-3, a ribosome-dependent ATPase. Here, we show that the antibiotic hygromycin B selectively inhibits the ATPase activity of RbbA. Other antibiotics with similar effects on miscoding, streptomycin and neomycin, as well as antibiotics that impair peptide bond synthesis and translocation, had little effect on the ATPase activity of RbbA on 70S ribosomes. Immunoblot analysis indicates that at physiological concentrations, hygromycin B selectively releases RbbA from 70S ribosomes. Hygromycin B protects G1494 and A1408 in the decoding region, and RbbA enhances the reactivity of A889 and G890 of the 16S rRNA switch helix region. Cross-linking and X-ray diffraction data have revealed that this helix switch and the decoding region are in close proximity. Mutations in the switch helix (889-890) region affect translational fidelity and translocation. The binding site of hygromycin B and its known dual effect on the fidelity of decoding and translocation suggest a model for the action of this drug on ribosomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".